Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning
Open accessAbstract
Analysing large numbers of brain samples can reveal minor, but statistically and biologically relevant variations in brain morphology that provide critical insights into animal behaviour, ecology and evolution. So far, however, such analyses have required extensive manual effort, which considerably limits the scope for comparative research. Here we used micro-CT imaging and deep learning to perform automated analyses of 3D image data from 187 honey bee and bumblebee brains. We revealed strong inter-individual variations in total brain size that are consistent across colonies and species, and may underpin behavioural variability central to complex social organisations. In addition, the bumblebee dataset showed a significant level of lateralization in optic and antennal lobes, providing a potential explanation for reported variations in visual and olfactory learning. Our fast, robust and user-friendly approach holds considerable promises for carrying out large-scale quantitative neuroanatomical comparisons across a wider range of animals. Ultimately, this will help address fundamental unresolved questions related to the evolution of animal brains and cognition.
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Automation using computer-vision and artificial intelligence methods can greatly reduce manual input.
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Perl, C. D., Coto, Z. N., Johnson, R., Johnson, M. G., Graber, L. C., Haas, J., Waters, J. S., Traniello, J. F. A., & Harrison, J. F. (2026) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2026.0387
- Authors
- Lösel, P. D., Monchanin, C., Lebrun, R., Jayme, A., Relle, J. J., Devaud, J.-M., Heuveline, V., & Lihoreau, M.
- Affiliations
- Australian National University (AU)
- Centre National de la Recherche Scientifique (FR)
- Heidelberg University (DE)
- Corresponding author
- Lösel, Philipp D.
- Monchanin, Coline
- ORCID
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2023-10-02
- Volume
- 19
- Issue
- 10
- Pages
- e1011529
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC10569549
- OpenAlex
- W4387251781
- Cited by
- 28
- References
- 72
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 11 · 2023: 4
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Update notices
- new_version (2023-10-12)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Agence Nationale de la Recherche (ANR-10-INBS-04, ANR-10-LABX-0004 and ANR-10-LABX-0020, 3DNaviBee ANR-19-CE37-0024)
- Bundesministerium für Bildung und Forschung (05K2013, 05K2016)
- Klaus Tschira Stiftung
- Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
- Deutsche Forschungsgemeinschaft (INST 35/1314-1 FUGG and INST 35/1134-1 FUGG)
- Ministère de l'Enseignement Supérieur et de la Recherche
- Agence de la Transition Ecologique (project LOTAPIS)
- European Commission (FEDER ECONECT MP0021763, ERC Cog BEE-MOVE GA101002644)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Insect and Arachnid Ecology and Behavior
- Physical Sciences › Mathematics › Geometry and Topology › Morphological variations and asymmetry
- Keywords
- Apis mellifera, bumblebees, brain size, brain asymmetry, laterality, optic lobe, antennal lobe, interindividual variability, deep learning, micro-CT, social behavior, cognitive evolution
- MeSH terms
- Deep Learning, Animals, Bees, Brain, Cognition, Organ Size, X-Ray Microtomography
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